Thursday, March 20, 2008

Given all of the environmental and health benefits from biotech foods, you would think that more supporters of organic production and 'sustainble agriculture' would be supportive of biotech crops. I'm not here to bash organic production, because I think that there is a market for everyone. However, research indicates that one shortfall of organic food is its exclusion of biotech/GM crops.

Europeans are very skeptical of biotech crops but accept nanotechnology. They also are very supportive of organic production. I wonder how most organic consumers view nanotechnology? Even if it benefits the environment?

On another note, most people probably don't know that even organic wheat varieties used for making organic pasta come from germplasm that was developted using mutation breeding i.e. introducing genetic variation by mutations casued by gamma rays. I wonder how they feel about that? What is more radical or more unnatural? If we really wanted 'all natural' corn, we'd have to eat the grass-like plant - teosinte- that's ultimately where we got modern corn.

Tuesday, March 18, 2008

I concluded my last entry on tax cuts and budget deficits by stating that there could be cases theoretically where Mankiw’s assumption about the failure of Ricardian Equivalence could be true.

I did provide some empirical evidence for a case where his conclusions about the detrimental effects from deficits failed to materialize as a result of the Regan tax cuts. What about other cases? If tax cuts lead to wealth effects and the failure of Ricardian Equivalence, then empirical evidence should show the following:

A correlation between tax cuts and an increase in demand, decrease in savings, and an increase in interest rates.

An increase in current account deficit ( if we are required to borrow from foreigners to finance tax cuts)

In an effort to see if these relationships hold up empirically, I provide the following literature review:

Monday, March 10, 2008

In my previous post, I concluded with findings by Mankiw that if consumers are uncertain about their future incomes and tax liability, Ricardian Equivalence may fail. This assumes that deficits are produced from the tax cuts.

What if there are no deficits? Then there will be no need to raise taxes in the future and no reduction in output in future periods.

Often the Regan tax cuts are cited as an example of poor public policy. The mantra goes that tax cuts for the rich generate deficits, which in turn lead to higher interest rates and a sour economy. The poor suffer, in addition to economic growth.

However, if government consumption stays constant, a tax cut now may not require an increase in the future if tax collections actually increase such that no deficit occurs. This may happen if marginal tax cuts increase the after tax value of the marginal product of labor and after tax marginal productivity of capital, leading to more production and output. With more output, a larger taxable revenue base results in more tax collections.

Lawrence Lindsey ( 1987) noted that for incomes greater than $200,000 per year, the Regan tax cuts lead to an increase in reported incomes and increased collections. For those earning > $200K per year, we saw the following increases in collections:

1982 – 3%1983 – 9%1984 – 23%

In his book ‘The Vision of the Annointed', Thomas Sowell points out the following: ( he obtained this info from ‘Budget of US Government: Historical Tables'. U.S. Government Printing Office, 1994.)

Each year, in the face of, and in the wake of large tax cuts, revenues increased. Therefore, it seems we have a situation with marginal tax rates where either Ricardian Equivalence will hold approximately, or tax cuts for the wealthy could actually have a simulative effect. I suppose we could reach a point ‘on the laffer curve’ where tax cuts would not lead to an increased revenue response. In that case, if RE fails as Mankiw believes, negative effects from deficits could occur.

About Me

My primary interests are in applied econometrics with applications related to genomics, nutrition, health, and the environment. I have a quantitative and analytical background in the areas of applied economics and statistical genetics. I leverage my training with experience in machine learning and predictive modeling using SAS, R, and Python to solve problems. I can understand and produce peer reviewed research and discuss the application with a scientist, sales representative, or the customer whose problem ultimately drives the analysis. I can code my own estimators, execute SQL queries, parse text files, and visualize a social network.